Dong Wang created SPARK-29816:
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Summary: Missing persist in
mllib.evaluation.BinaryClassificationMetrics.recallByThreshold()
Key: SPARK-29816
URL: https://issues.apache.org/jira/browse/SPARK-29816
Project: Spark
Issue Type: Improvement
Components: MLlib
Affects Versions: 2.4.3
Reporter: Dong Wang
The rdd scoreAndLabels.combineByKey is used by two actions: sortByKey and
count(), so it needs to be persisted.
{code:scala}
val counts = scoreAndLabels.combineByKey(
createCombiner = (label: Double) => new BinaryLabelCounter(0L, 0L) +=
label,
mergeValue = (c: BinaryLabelCounter, label: Double) => c += label,
mergeCombiners = (c1: BinaryLabelCounter, c2: BinaryLabelCounter) => c1
+= c2
).sortByKey(ascending = false) // first use
val binnedCounts =
// Only down-sample if bins is > 0
if (numBins == 0) {
// Use original directly
counts
} else {
val countsSize = counts.count() //second use
{scala}
This issue is reported by our tool CacheCheck, which is used to dynamically
detecting persist()/unpersist() api misuses.
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